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Description

The following analytic detects the creation of privileged pods in Kubernetes. It identifies this behavior by monitoring Kubernetes Audit logs for the creation of pods with root privileges. This behavior is worth identifying for a SOC as it could potentially allow an attacker to escalate privileges, exploit the kernel, and gain full access to the host's namespace and devices. The impact of such an attack could be severe, leading to unauthorized access to sensitive information, data breaches, and service disruptions.

  • Type: Anomaly
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

  • Last Updated: 2023-12-14
  • Author: Patrick Bareiss, Splunk
  • ID: 9af5c1b9-8243-4225-ac29-b261e43f12bb

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1204 User Execution Execution
Kill Chain Phase
  • Installation
NIST
  • DE.AE
CIS20
  • CIS 13
CVE
1
2
3
4
5
`kube_audit` objectRef.resource=pods verb=create OR verb=update requestObject.metadata.annotations.kubectl.kubernetes.io/last-applied-configuration=*\"privileged\":true* 
| fillnull 
| stats count values(user.groups{}) as user_groups by kind objectRef.name objectRef.namespace objectRef.resource requestObject.kind responseStatus.code sourceIPs{} stage user.username userAgent verb requestObject.metadata.annotations.kubectl.kubernetes.io/last-applied-configuration 
| rename sourceIPs{} as src_ip, user.username as user 
| `kubernetes_create_or_update_privileged_pod_filter` 

Macros

The SPL above uses the following Macros:

:information_source: kubernetes_create_or_update_privileged_pod_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • user.groups{}
  • kind
  • objectRef.name
  • objectRef.namespace
  • objectRef.resource
  • requestObject.kind
  • requestObject.spec.type
  • responseStatus.code
  • sourceIPs{}
  • stage
  • user.username
  • userAgent
  • verb
  • requestObject.metadata.annotations.kubectl.kubernetes.io/last-applied-configuration

How To Implement

The detection is based on data that originates from Kubernetes Audit logs. Ensure that audit logging is enabled in your Kubernetes cluster. Kubernetes audit logs provide a record of the requests made to the Kubernetes API server, which is crucial for monitoring and detecting suspicious activities. Configure the audit policy in Kubernetes to determine what kind of activities are logged. This is done by creating an Audit Policy and providing it to the API server. Use the Splunk OpenTelemetry Collector for Kubernetes to collect the logs. This doc will describe how to collect the audit log file https://github.com/signalfx/splunk-otel-collector-chart/blob/main/docs/migration-from-sck.md.

Known False Positives

unknown

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
49.0 70 70 Kubernetes privileged pod created by user $user$.

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Reference

Test Dataset

Replay any dataset to Splunk Enterprise by using our replay.py tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range

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